Chapter 4: Analysis and Discussion
4.1 Efficiency Measurement and DEA Model Application
4.1.2 The Results Summary for Efficiency Measurement Using DEA Model
inputs and two outputs. While the indicators chosen to correspond to those used by Vitezi c et al. (2016) in one of their models, this study is a follow-up that includes new and additional criteria. To begin, it is based on a revised and extended period for selected input and output indicators. Moreover secondly, it incorporates the CCR model. Thus, the study focuses on three types of efficiency – technical, pure technical, and scale efficiency – to ascertain whether the source of inefficiency is an inefficient operation or adverse conditions. Only when the source of inefficiency is identified can appropriate measures and actions be proposed and implemented. Table 4.1 contains summary statistics for the sample used, aggregated over time and across units. The summary data exhibit a high degree of variability, making it impossible to draw firm conclusions about the units' average performance over a given year. The conclusion is highly dependent on the statistical measure selected. The following example demonstrates this.
Table 4.1
Data summary statistics, 2011–2021, in Healthcare Sector in the GCC Region
Variables Years Mean Median SD Min. Max. CV(%)
Input Salaries 2011 - 2021 220.201 160.520 37.786 0.280 811.176 0.17 Direct Cost 2011 - 2021 561.057 616.577 196.398 1.479 3259.947
0.35 Investments 2011 - 2021 1373.534 1000.289 382.424 0.102 8776.032
0.28 Output Revenue 2011 - 2021 1133.245 1031.721 345.609 8.688 7201.500
0.30 Net Income 2011 - 2021 171.838 103.694 26.704 0.061 1225.932
0.16
Financial performance-efficiency nexus in The Healthcare Sector in The GCC Region: A nonparametric
Compared to 2017 and 2018, 2016 has the lowest minimum values for all three inputs. Since smaller quantities of inputs are desirable, this year would be relatively successful. At the same time, that year is distinguished by the highest maximum values for two inputs and the lowest maximum output value, which is both undesirable and indicates that this was the worst year. The actual result is somewhere in between, as evidenced by the average values of the variables, which for this year range from the most favourable (lowest average salaries) to the least good (highest average salaries) (highest average investments and lowest average total revenues).
Nonetheless, the DEA will address, among other things, which year was the most successful and which was the least successful, i.e., rank their success. Although correlations between the selected indicators are not the primary focus of this study, the solid positive relationship between average salaries and average total revenues is worth considering as a rationale for possible changes. The initial analysis stage described in the following section revealed considerable variation in the results obtained from the CCR and BCC models Table 4.2 and Figure, which can be attributed to the return effect concerning the range of unit activities. This can be interpreted as confirmation of the BCC model's superior suitability to the CCR model for the process analyzed in this paper. However, because one of the objectives of this study is to differentiate between various types of inefficiency, both CCR and BCC models were used. The models are input-oriented, which means that they seek to minimize input in exchange for a given output level.
Table 4.2
Summary statistics for the input-oriented CCR and BCC models.
The majority of firms surveyed using the DEA approach operate at an acceptable level of efficiency, with BCC scores ranging from to, whereas CCR efficiency scores range from to. This implies that firms' input costs should be reduced by between 5%
and 36% while maintaining the same output level. To reach 1.00, they are operating at their optimal efficiency level as output increases, whereas the others remain inefficient, despite their average CCR, BCC, and scale efficiency being close to 1.00.
This implies that most large firms and their small counterparts operate at suboptimal efficiency levels. As a result, necessary measures should be taken to enhance operational performance and efficiency, as detailed in Table 8, including the efficient input and output target percentages.
Summary statistics for the input-oriented BCC model BCC Model
2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
Number of efficient Companies 11 8 7 7 8 6 9 4 5 9 3
Number of inefficient Companies 1 4 5 5 4 6 3 8 7 3 9
Average efficiency score 0.9761 0.9707 0.9860 0.9873 0.9821 0.9280 0.9779 0.9568 0.9626 0.9565 0.9686
Standard deviation 0.0827 0.0654 0.0212 0.0294 0.0433 0.1103 0.0420 0.0608 0.0492 0.0820 0.0433
Minimum efficacy score 0.7134 0.7822 0.9401 0.8993 0.8558 0.6547 0.8918 0.7957 0.8563 0.7663 0.8541
Number below average efficiency 1 3 4 2 2 4 3 4 4 3 5
Summary statistics for the input-oriented CCR model CCR Model
2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
Number of efficient Companies 9 5 5 5 4 3 6 1 1 3 2
Number of inefficient Companies 3 7 7 7 8 9 6 11 11 9 10
Average efficiency score 0.9007 0.9534 0.9642 0.9294 0.9003 0.8586 0.9256 0.8878 0.8794 0.8583 0.9146
Standard deviation 0.2210 0.0901 0.0481 0.1389 0.1431 0.1861 0.1272 0.1069 0.1046 0.1168 0.0884
Minimum efficacy score 0.2643 0.7624 0.8541 0.5359 0.5335 0.4522 0.5645 0.6628 0.6686 0.6771 0.7413
Number below average efficiency 3 2 4 2 4 5 4 5 7 7 5
Financial performance-efficiency nexus in The Healthcare Sector in The GCC Region: A nonparametric
Figure 3
Figure 4
0 2 4 6 8 10 12
2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
Chart of Efficient Firms with CCR & BCC (2011-2021)
CCR Model BCC Model
0.7500 0.8000 0.8500 0.9000 0.9500 1.0000
2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
Average of Efficiency Score CCR & BCC Models
CCR Model BCC Model
As a result, necessary measures should be taken to enhance operational performance and efficiency, as detailed in (Table 8), including the efficient input and output target percentages. The empirical evidence in (Table 6) indicates that inefficient businesses require improvement. The management must be strengthened through increased investment and a greater emphasis on revenue generation (Figure 5). This study examines each input for financial ratio approaches and compares it sequentially to the benchmark (Figure 3). However, by combining DEA-CCR and DEA-BCC with an input-oriented assumption, we can estimate the targets for measuring and explaining each firm's performance (Figure 5).
Table 8
Efficient Input and Output Target percentage to improve to efficient level for 2021
# DMUs
Efficient Input Target Efficient Output Target Salaries Direct
costs Investments Revenue Net Income
1 ALHAMMAD 5% 5% 5% 5% 5%
2 AADC AB 20% 7% 16% 33% 4%
3 DALLAH AB 6% 6% 6% 6% 6%
4 SULAIMAN 7% 3% 12% 23% 16%
5 MEH AB 6% 15% 19% 8% 73%
6 MOUWASAT 4% 11% 7% 6% 2%
7 CARE AB 3% 6% 27% 1% 2%
8 CHEMICAL AB 7% 8% 0% 5% 1%
9 SPIMACO AB 18% 23% 21% 21% 10%
10 MIDAN KK 18% 6% 24% 10% 22%
11 YIACO KK 7% 9% 10% 33% 8%
12 ATC KK 4% 5% 36% 23% 2%
Financial performance-efficiency nexus in The Healthcare Sector in The GCC Region: A nonparametric
Figure 5
Inefficient sources results from input to be Target for the Healthcare firms
4.2 Financial Performance of Healthcare Firms and Subsidiaries